Fraud Model Consulting Lead · Plaid

Fri, 24 Apr 2026 16:12:28 GMT
Engineering

Plaid · New York · $190,800-$286,800 per year · hybrid

We believe that the way people interact with their finances will drastically improve in the next few years. We're dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products.

Our Fraud team's mission is to help companies detect and prevent fraud using financial network data. We believe that transaction patterns, device signals, and behavioural data are an underleveraged tool in fraud prevention.

The Fraud Consulting Lead is responsible for building and maturing our retro-as-a-service and POC program and driving adoption of our fraud products. The role sits between our data team and the customer (i.e., the role will not build the models, but will need to understand the output well enough to clearly and compellingly present the business case and work with technical stakeholders and customers.)

Responsibilities:

Own the retro and POC process end-to-end and collaborate with customers and internal stakeholders at Plaid

Partner closely with customers to help them understand the ROI of Protect and make recommendations for implementing our fraud products

Drive post-retro follow-through to convert retro results into production usage

Serve as a feedback loop between customers and product to drive our Protect roadmap

Qualifications:

5-10 years of experience in a customer-facing analytical role in fintech, financial services, or a related domain (e.g., software/tech)

Experience working closely with data science teams

Experience managing consultative customer engagements where you owned the deliverable and the relationship

Comfort interpreting ML model output (e.g., precision/recall, score distributions) and explaining it to a non-technical audience

Nice to have: Background in data science or ML engineering, particularly on a fraud or risk team

Nice to have: Experience in fraud, identity, or risk , either from a fraud prevention vendor, a fraud team at a bank or fintech, or consulting on risk engagements